{ "_id": "6a106ee9acfb0bcc41cab4d4", "Package": "SplitKnockoff", "Type": "Package", "Title": "Split Knockoffs for Structural Sparsity", "Version": "1.1", "Date": "2022-02-20", "Author": "Haoxue Wang [aut, cre] (Development of the whole packages),\nYang Cao [aut] (Revison of this package), Xinwei Sun [aut]\n(Original ideas about the package), Yuan Yao [aut] (Testing for\nthe package and management of the development)", "Authors@R": "c(person(\"Haoxue\", \"Wang\", role = c(\"aut\",\"cre\"),\ncomment=\"Development of the whole packages\",\nemail=\"haoxwang@student.ethz.ch\"),\nperson(\"Yang\", \"Cao\", role = c(\"aut\"),\ncomment=\"Revison of this package\"),\nperson(\"Xinwei\", \"Sun\", role = c(\"aut\"),\ncomment=\"Original ideas about the package\"),\nperson(\"Yuan\", \"Yao\", role = c(\"aut\"),\ncomment=\"Testing for the package and management of the development\"))", "Maintainer": "Haoxue Wang ", "Description": "Split Knockoff is a data adaptive variable selection\nframework for controlling the (directional) false discovery\nrate (FDR) in structural sparsity, where variable selection on\nlinear transformation of parameters is of concern. This\nproposed scheme relaxes the linear subspace constraint to its\nneighborhood, often known as variable splitting in\noptimization. Simulation experiments can be reproduced\nfollowing the Vignette. We include data (both .mat and .csv\nformat) and application with our method of Alzheimer's Disease\nstudy in this package. 'Split Knockoffs' is first defined in\nCao et al. (2021) .", "URL": "https://github.com/wanghaoxue0/SplitKnockoff", "BugReports": "https://github.com/wanghaoxue0/SplitKnockoff/issues", "Encoding": "UTF-8", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "RoxygenNote": "7.1.2", "License": "MIT + file LICENSE", "Packaged": { "Date": "2026-05-07 07:51:28 UTC", "User": "root" }, "Repository": "https://wanghaoxue0.r-universe.dev", "Date/Publication": "2022-02-21 14:23:56 UTC", "RemoteUrl": "https://github.com/wanghaoxue0/splitknockoff", "RemoteRef": "HEAD", "RemoteSha": "259761699f55a1b4bf60fddc4c659263812d341f", "MD5sum": "4132531896756105b04b17cb139a2a0e", "_user": "wanghaoxue0", "_type": "src", "_file": "SplitKnockoff_1.1.tar.gz", "_fileid": "4855e0ad4eb5cf543cb63f702091cabbd91049d5a25de703e9615f986b3de59a", "_filesize": 1240290, "_sha256": "4855e0ad4eb5cf543cb63f702091cabbd91049d5a25de703e9615f986b3de59a", "_created": "2026-05-07T07:51:28.000Z", "_published": "2026-05-22T14:57:45.794Z", "_distro": "noble", "_jobs": [ { "job": 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"version": "0.8", "date": "2021-09-13" }, { "version": "1.0", "date": "2021-11-02" }, { "version": "1.1", "date": "2022-02-20" }, { "version": "1.2", "date": "2022-03-18" }, { "version": "2.1", "date": "2024-10-14" } ], "_exports": [ "canonicalSVD", "hittingpoint", "normc", "simu_eval", "simu_unit", "sk.create", "sk.decompose", "sk.filter", "sk.select", "W_sign", "W_support" ], "_help": [ { "page": "canonicalSVD", "title": "singular value decomposition", "topics": [ "canonicalSVD" ] }, { "page": "hittingpoint", "title": "hitting point calculator on a given path", "topics": [ "hittingpoint" ] }, { "page": "normc", "title": "default normalization function for matrix", "topics": [ "normc" ] }, { "page": "simu_eval", "title": "functions for evaluating simulations", "topics": [ "simu_eval" ] }, { "page": "simu_unit", "title": "default unit for simulations", "topics": [ "simu_unit" ] }, { "page": "sk.create", "title": "generate split knockoff copies", "topics": [ "sk.create" ] }, { "page": "sk.decompose", "title": "make SVD as well as orthogonal complements", "topics": [ "sk.decompose" ] }, { "page": "sk.filter", "title": "Split Knockoff filter for structural sparsity", "topics": [ "sk.filter" ] }, { "page": "sk.select", "title": "split knockoff selector given W statistics", "topics": [ "sk.select" ] }, { "page": "W_sign", "title": "W statistics generator for directional FDR control", "topics": [ "W_sign" ] }, { "page": "W_support", "title": "W statistics generator for FDR control", "topics": [ "W_support" ] } ], "_readme": "https://github.com/wanghaoxue0/splitknockoff/raw/HEAD/README.md", "_rundeps": [ "cli", "codetools", "cpp11", "farver", "foreach", "ggplot2", "glmnet", "glue", "gtable", "isoband", "iterators", "labeling", "latex2exp", "lattice", "lifecycle", "MASS", "Matrix", "mvtnorm", "R6", "RColorBrewer", "Rcpp", "RcppEigen", "rlang", "RSpectra", "S7", "scales", "shape", "survival", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "Splitknockoff.Rmd", "filename": "Splitknockoff.html", "title": "Splitknockoff", "engine": "knitr::rmarkdown", "headings": [ "Vignette for Splitknockoff", "Introduction", "Key function", "function involved frequently", "For reproduction of the simulation, you can see the code as the following.", "simulation details", "Install all the packages and library them.", "set the parameter for the simulation", "generate D and X", "package mvtnorm needed for this generation, please install it in advance", "generate beta and gamma", "generate noise and y", "key step", "for Figure 2a, 2b, 2d, 2e, 2g and 2h of the paper simulation", "Alzheimer’s Disease application", "Disclose important lesion regions in brains associated with the disease", "Connections between neighboring regions of high contrast variations during disease progression.", "For your consideration" ], "created": "2022-02-21 13:40:45", "modified": "2022-02-21 13:40:45", "commits": 1 } ], "_score": 4.176091259055681, "_indexed": true, 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